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Machine Intelligence I (supervised methods)

Lupe

General information

  • The course Machine Intelligence I will be offered during WS 20/21 in an online format. However, the exam at the end of the semester is a written exam which will take place on-site. Remote online exams will not be possible.
  • The courses Machine Intelligence I and II can be heard independently. You do not have to take one in order to take the other.
  • The lecture and tutorials are held in English.
  • The course is open to TU students as well as exchange students and visiting students. Non-TU students should apply to a Neben-/Gasthörschaft to gain access to the course material.
  • No formal registration is required to attend the course. The registration is only relevant for the exam.
  • The exam registration procedure is announced in the first lecture. Prior registration/reservation is not possible and not necessary.
  • Information regarding the material, tutorials and the exam can be found on the ISIS page (see panel on the right).



Topics covered

  • Connectionist neuron
  • Feed-forward neural networks
  • Learning and generalization
  • Deep Learning
  • Recurrent neural architectures
  • Radial basis function networks
  • Elements of statistical learning theory
  • Structural risk minimization
  • Support vector machines
  • Uncertainty and inference
  • Bayesian networks
  • Bayesian Inference and Neural Networks
  • Reinforcement learning



Prerequisites

  • Solid mathematical knowledge: analysis, linear algebra, probability calculus and statistics. We emphasize this requirement because the course deals with the theoretical aspects and mathematical formulations of the learning algorithms.
  • Basic programming skills, preferably Python, R, Matlab, or Julia. The programming skills are relevant for solving the programming exercises.



Target Audience / Assessment and Grading

Program
Form of Assessment
MSc in Computational Neuroscience
The two courses (Machine Intelligence I and II) form a single module (12 ECTS).

assignments & oral exam
MSc in Computer Science
Each of the two courses (Machine Intelligence I or II) can be taken as a separate module (6 ECTS).

written exam (no assignments during the course)
Other study programs (e.g., mathematics, natural, and engineering sciences)
Each of the two courses (Machine Intelligence I or II) can be taken as a separate module (6 ECTS).

written exam (no assignments during the course)

 

For further information please consult  (lecturer, in charge) or  (assistant).

Zusatzinformationen / Extras

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Auxiliary Functions

Lecture

Machine Intelligence I
0434 L 866
Lecture

Lecturer: Klaus Obermayer

Period:
from 02.11.2020

Location: digital

ISIS

Tutorials

Exercise

Lecturer: Youssef Kashef

Period:
from 02.11.2020

Location: digital



ISIS